RESUMO
INTRODUCTION: Functional assessment of arterial load by dynamic arterial elastance (Eadyn), defined as the ratio between pulse pressure variation (PPV) and stroke volume variation (SVV), has recently been shown to predict the arterial pressure response to volume expansion (VE) in hypotensive, preload-dependent patients. However, because both SVV and PPV were obtained from pulse pressure analysis, a mathematical coupling factor could not be excluded. We therefore designed this study to confirm whether Eadyn, obtained from two independent signals, allows the prediction of arterial pressure response to VE in fluid-responsive patients. METHODS: We analyzed the response of arterial pressure to an intravenous infusion of 500 ml of normal saline in 53 mechanically ventilated patients with acute circulatory failure and preserved preload dependence. Eadyn was calculated as the simultaneous ratio between PPV (obtained from an arterial line) and SVV (obtained by esophageal Doppler imaging). A total of 80 fluid challenges were performed (median, 1.5 per patient; interquartile range, 1 to 2). Patients were classified according to the increase in mean arterial pressure (MAP) after fluid administration in pressure responders (≥ 10%) and non-responders. RESULTS: Thirty-three fluid challenges (41.2%) significantly increased MAP. At baseline, Eadyn was higher in pressure responders (1.04 ± 0.28 versus 0.60 ± 0.14; P < 0.0001). Preinfusion Eadyn was related to changes in MAP after fluid administration (R (2) = 0.60; P < 0.0001). At baseline, Eadyn predicted the arterial pressure increase to volume expansion (area under the receiver operating characteristic curve, 0.94; 95% confidence interval (CI): 0.86 to 0.98; P < 0.0001). A preinfusion Eadyn value ≥ 0.73 (gray zone: 0.72 to 0.88) discriminated pressure responder patients with a sensitivity of 90.9% (95% CI: 75.6 to 98.1%) and a specificity of 91.5% (95% CI: 79.6 to 97.6%). CONCLUSIONS: Functional assessment of arterial load by Eadyn, obtained from two independent signals, enabled the prediction of arterial pressure response to fluid administration in mechanically ventilated, preload-dependent patients with acute circulatory failure.
Assuntos
Pressão Arterial/fisiologia , Velocidade do Fluxo Sanguíneo/fisiologia , Hidratação/métodos , Respiração Artificial/métodos , Volume Sistólico/fisiologia , Idoso , Débito Cardíaco/fisiologia , Feminino , Hidratação/tendências , Humanos , Masculino , Pessoa de Meia-Idade , Valor Preditivo dos Testes , Estudos Prospectivos , Respiração Artificial/tendênciasRESUMO
INTRODUCTION: The reliability of pulse pressure analysis to estimate cardiac output is known to be affected by arterial load changes. However, the contribution of each aspect of arterial load could be substantially different. In this study, we evaluated the agreement of eight non-commercial algorithms of pulse pressure analysis for estimating cardiac output (PPCO) with esophageal Doppler cardiac output (EDCO) during acute changes of arterial load. In addition, we aimed to determine the optimal arterial load parameter that could detect a clinically significant difference between PPCO and the EDCO. METHODS: We included mechanically ventilated patients monitored with a prototype esophageal Doppler (CardioQ-Combi™, Deltex Medical, Chichester, UK) and an indwelling arterial catheter who received a fluid challenge or in whom the vasoactive medication was introduced or modified. Initial calibration of PPCO was made with the baseline value of EDCO. We evaluated several aspects of arterial load: total systemic vascular resistance (TSVR=mean arterial pressure [MAP]/EDCO*80), net arterial compliance (C=EDCO-derived stroke volume/pulse pressure), and effective arterial elastance (Ea=0.9*systolic blood pressure/EDCO-derived stroke volume). We compared CO values with Bland-Altman analysis, four-quadrant plot and a modified polar plot (with least significant change analysis). RESULTS: A total of 16,964-paired measurements in 53 patients were performed (median 271; interquartile range: 180-415). Agreement of all PPCO algorithms with EDCO was significantly affected by changes in arterial load, although the impact was more pronounced during changes in vasopressor therapy. When looking at different parameters of arterial load, the predictive abilities of Ea and C were superior to TSVR and MAP changes to detect a PPCO-EDCO discrepancy≥10% in all PPCO algorithms. An absolute Ea change>8.9±1.7% was associated with a PPCO-EDCO discrepancy≥10% in most algorithms. CONCLUSIONS: Changes in arterial load profoundly affected the agreement of PPCO and EDCO, although the contribution of each aspect of arterial load to the PPCO-EDCO discrepancies was significantly different. Changes in Ea and C mainly determined PPCO-EDCO discrepancy.